Triple
T6891726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Basque Country |
E159063
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Anglet |
E168470
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Anglet | Statement: [Northern Basque Country, hasCity, Anglet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anglet Context triple: [Northern Basque Country, hasCity, Anglet]
-
A.
Anglet
chosen
Anglet is a coastal city in southwestern France, situated between Bayonne and Biarritz in the French Basque Country and known for its Atlantic beaches and surf culture.
-
B.
Villeneuve d’Ascq
Villeneuve d’Ascq is a suburban city in northern France near Lille, known for its universities, technology parks, and modernist urban planning.
-
C.
Boulogne-sur-Mer
Boulogne-sur-Mer is a coastal city and major fishing port in northern France, located on the English Channel in the Pas-de-Calais department.
-
D.
Pont-l’Évêque
Pont-l’Évêque is a small historic town in Normandy, France, best known for giving its name to the traditional soft cow’s milk cheese Pont-l’Évêque.
-
E.
Boulogne
Boulogne is a French football club known for being one of the early professional teams in N’Golo Kanté’s career.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6883568c8819081db6407e892cccc |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d92ecbdc8190992f9c7f4f33f4c4 |
completed | March 27, 2026, 7:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7942be8708190bad44a9966884515 |
completed | March 28, 2026, 8:41 a.m. |
Created at: March 27, 2026, 2:24 p.m.